PyIRoGlass v0.2.0 released!

UnitTests/test_concentration.py

@@ -4,7 +4,6 @@
 import PyIRoGlass as pig
 
 
-
 class test_conc_outputs_h2ot(unittest.TestCase):
 
     def setUp(self): 
@@ -89,14 +88,41 @@ def setUp(self):
         self.P_room = 1 
         self.decimalPlace = 5
 
-    def test_concentration(self):
+    def test_concentration(self): # OL53
 
         density_epsilon, mega_spreadsheet = pig.Concentration_Output(self.PH, self.N, self.thickness, self.MI_Composition, self.T_room, self.P_room)
         expected_H2O = 4.03892743514451
         expected_CO2 = 713.3372363302
         self.assertAlmostEqual(float(mega_spreadsheet['H2OT_MEAN']), expected_H2O, self.decimalPlace, msg="H2Ot test values from the Concentration_Output equation do not agree")
         self.assertAlmostEqual(float(mega_spreadsheet['CO2_MEAN']), expected_CO2, self.decimalPlace, msg="CO2m test values from the Concentration_Output equation do not agree")
 
+class test_conc_outputs_saturated(unittest.TestCase): # OL49
+
+    def setUp(self):
+
+        self.MI_Composition = pd.DataFrame({'SiO2': [52.34], 'TiO2': [1.04], 'Al2O3': [17.92], 'Fe2O3': [1.93], 'FeO': [7.03],
+                              'MnO': [0.20], 'MgO': [3.63], 'CaO': [7.72], 'Na2O': [4.25], 'K2O': [0.78], 'P2O5': [0.14]},
+                              index=['AC4_OL49_021920_30x30_H2O_a'])
+        self.PH = pd.DataFrame({'PH_3550_M': [2.17224950314409], 'PH_3550_STD': [0.00220916618090868], 'H2OT_3550_SAT?': ['*'], 'PH_1635_BP': [0.658349188362703],
+                   'PH_1635_STD': [0.00307592496318145], 'PH_1515_BP': [0.106864326434928], 'PH_1515_STD': [0.0035555642315165],
+                   'PH_1430_BP': [0.109429135799036], 'PH_1430_STD': [0.00405404583060287], 'PH_5200_M': [0.0249095178877388], 'PH_5200_STD': [0.000801149484503151], 
+                   'PH_4500_M': [0.014569658580663], 'PH_4500_STD': [0.0000638336854435091], 'S2N_P5200': [12.1959313061391], 'S2N_P4500': [8.15732983956986],
+                   'ERR_5200': ['-'], 'ERR_4500': ['-']}, index=['AC4_OL49_021920_30x30_H2O_a'])
+        self.thickness = pd.DataFrame({'Thickness': [91.25], 'Sigma_Thickness': [3]}, index=['AC4_OL49_021920_30x30_H2O_a'])
+        self.N = 500000
+        self.T_room = 25 
+        self.P_room = 1 
+        self.decimalPlace = 5
+
+    def test_concentration(self):
+
+        density_epsilon, mega_spreadsheet = pig.Concentration_Output(self.PH, self.N, self.thickness, self.MI_Composition, self.T_room, self.P_room)
+        expected_H2O = 2.54389275724829
+        expected_CO2 = 738.262088884613
+        self.assertAlmostEqual(float(mega_spreadsheet['H2OT_MEAN']), expected_H2O, self.decimalPlace, msg="H2Ot test values from the saturated Concentration_Output equation do not agree")
+        self.assertAlmostEqual(float(mega_spreadsheet['CO2_MEAN']), expected_CO2, self.decimalPlace, msg="CO2m test values from the saturated Concentration_Output equation do not agree")
+
+
 
 if __name__ == '__main__':
      unittest.main()

UnitTests/test_fittingfunc.py

@@ -1,10 +1,10 @@
+import os
 import unittest
 import numpy as np
 import pandas as pd
 import PyIRoGlass as pig
 
 
-
 class test_fitting_functions(unittest.TestCase):
 
     def setUp(self): 
@@ -86,5 +86,21 @@ def test_MCMC(self):
         self.assertAlmostEqual(result_CO2_1515, expected_CO2_1515, self.decimalPlace-3, msg="CO2_1515 peak height test and expected values from the Run_All_Spectra function do not agree")
 
 
+    def test_MCMC_exportpath(self):
+
+        temp_export_path = "temp_test_dir"
+        os.makedirs(temp_export_path, exist_ok=True)
+
+        Volatiles_DF, failures = pig.Run_All_Spectra(self.sample_dfs_dict, temp_export_path)
+        Volatiles_DF.to_csv(os.path.join(temp_export_path, "output.csv"))
+
+        # Check if the result was exported correctly
+        self.assertTrue(os.path.exists(os.path.join(temp_export_path, "output.csv")))
+
+        # Cleanup
+        os.remove(os.path.join(temp_export_path, "output.csv"))
+        os.rmdir(temp_export_path)
+
+
 if __name__ == '__main__':
      unittest.main()

UnitTests/test_plotting.py

@@ -5,12 +5,35 @@
 import pandas as pd
 import sys
 import PyIRoGlass as pig
-
+import matplotlib.pyplot as plt
 
 
 class test_plotting_trace(unittest.TestCase):
 
-    def test_trace(self):
+    @patch("matplotlib.pyplot.Figure.savefig")
+    def test_trace_savefile(self, mock_savefig):
+
+        pnames   = ['B_mean',"B_PC1","B_PC2","B_PC3","B_PC4",'G1430_peak','G1430_std','G1430_amp',
+                    'G1515_peak','G1515_std','G1515_amp','H1635_mean','H1635_PC1','H1635_PC2','m','b']
+
+        texnames = ['$\overline{B}$',"$\overline{B}_{PC1}$","$\overline{B}_{PC2}$","$\overline{B}_{PC3}$",'$\overline{B}_{PC4}$',
+                    '$\mu_{1430}$','$\sigma_{1430}$','$a_{1430}$','$\mu_{1515}$','$\sigma_{1515}$','$a_{1515}$',
+                    '$\overline{H_{1635}}$','$\overline{H_{1635}}_{PC1}$','$\overline{H_{1635}}_{PC2}$','$m$','$b$']
+
+        file_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../docs/examples/transmission_ftir/NPZTXTFILES/RESULTS/AC4_OL53_101220_256s_30x30_a.npz') 
+        mcmc_npz = np.load(file_path)
+
+        fig = pig.trace(mcmc_npz['posterior'], title = 'AC4_OL53_101220_256s_30x30_a', zchain=mcmc_npz['zchain'], burnin=mcmc_npz['burnin'], pnames=texnames, savefile='dummy_filename.png')
+
+        # Check if savefig was called with the correct filename
+        mock_savefig.assert_called_once()
+        args, kwargs = mock_savefig.call_args
+        assert 'dummy_filename.png' in args[0]
+        plt.close('all')
+
+
+    @patch("matplotlib.pyplot.Figure.savefig")
+    def test_trace_nosavefile(self, mock_savefig):
 
         pnames   = ['B_mean',"B_PC1","B_PC2","B_PC3","B_PC4",'G1430_peak','G1430_std','G1430_amp',
                     'G1515_peak','G1515_std','G1515_amp','H1635_mean','H1635_PC1','H1635_PC2','m','b']
@@ -24,6 +47,11 @@ def test_trace(self):
 
         fig = pig.trace(mcmc_npz['posterior'], title = 'AC4_OL53_101220_256s_30x30_a', zchain=mcmc_npz['zchain'], burnin=mcmc_npz['burnin'], pnames=texnames)
 
+        # Check if savefig was never called
+        mock_savefig.assert_not_called()
+        plt.close('all')
+
+
 class test_plotting_modelfit(unittest.TestCase):
 
     def setUp(self): 
@@ -37,7 +65,32 @@ def setUp(self):
         self.spec_mc3 = self.df_lim['Absorbance'].to_numpy()
         self.decimalPlace = 5
 
-    def test_modelfit(self):
+
+    def test_modelfit_savefile(self, mock_savefig):
+
+        file_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../src/PyIRoGlass/BaselineAvgPC.npz') 
+        wavenumber = pig.Load_Wavenumber(file_path)
+
+        pnames   = ['B_mean',"B_PC1","B_PC2","B_PC3","B_PC4",'G1430_peak','G1430_std','G1430_amp',
+                    'G1515_peak','G1515_std','G1515_amp','H1635_mean','H1635_PC1','H1635_PC2','m','b']
+
+        texnames = ['$\overline{B}$',"$\overline{B}_{PC1}$","$\overline{B}_{PC2}$","$\overline{B}_{PC3}$",'$\overline{B}_{PC4}$',
+                    '$\mu_{1430}$','$\sigma_{1430}$','$a_{1430}$','$\mu_{1515}$','$\sigma_{1515}$','$a_{1515}$',
+                    '$\overline{H_{1635}}$','$\overline{H_{1635}}_{PC1}$','$\overline{H_{1635}}_{PC2}$','$m$','$b$']
+
+        file_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../docs/examples/transmission_ftir/NPZTXTFILES/RESULTS/AC4_OL49_021920_30x30_H2O_a.npz') 
+        mcmc_npz = np.load(file_path)
+
+        fig = pig.modelfit(self.spec_mc3, np.ones_like(self.spec_mc3) * 0.01, wavenumber, mcmc_npz['best_model'], title = 'AC4_OL49_021920_30x30_H2O_a', savefile='dummy_filename.png')
+
+        # Check if savefig was called with the correct filename
+        mock_savefig.assert_called_once()
+        args, kwargs = mock_savefig.call_args
+        assert "dummy_filename.png" in args[0]
+        plt.close('all')
+
+
+    def test_modelfit_nosavefile(self, mock_savefig):
 
         file_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../src/PyIRoGlass/BaselineAvgPC.npz') 
         wavenumber = pig.Load_Wavenumber(file_path)
@@ -53,6 +106,10 @@ def test_modelfit(self):
         mcmc_npz = np.load(file_path)
 
         fig = pig.modelfit(self.spec_mc3, np.ones_like(self.spec_mc3) * 0.01, wavenumber, mcmc_npz['best_model'], title = 'AC4_OL49_021920_30x30_H2O_a')
+
+        # Check if savefig was called with the correct filename
+        mock_savefig.assert_not_called()
+        plt.close('all')
 
 
 if __name__ == '__main__':

UnitTests/test_thickness.py

@@ -41,7 +41,7 @@ def test_peak_identification(self):
         peak_search_width = 10
         wn_high = 2700
         wn_low = 2100
-        peaks, troughs = pig.PeakID(self.df, wn_high, wn_low, filename=self.file, plotting=False, savgol_filter_width=savgol_filter_width, smoothing_wn_width = smoothing_wn_width, remove_baseline = True, peak_heigh_min_delta = peak_heigh_min_delta, peak_search_width = peak_search_width)
+        peaks, troughs = pig.PeakID(self.df, wn_high, wn_low, filename=self.file, plotting=True, savgol_filter_width=savgol_filter_width, smoothing_wn_width = smoothing_wn_width, remove_baseline = True, peak_heigh_min_delta = peak_heigh_min_delta, peak_search_width = peak_search_width)
         expected_peak_loc = 2138.76
         self.assertAlmostEqual(float(peaks[0, 0]), expected_peak_loc, self.decimalPlace-2, msg="Peak location test and expected values from the Peak_ID function do not agree")
 

docs/FAQs.rst

@@ -2,4 +2,4 @@
 FAQs and Troubleshooting
 ========================
 
-``PyIRoGlass`` has been tested by several users, but it is still very possible that there are errors. Please alert `Sarah Shi <sarah.shi@columbia.edu>`_ to any errors or bugs within the code and/or raise an issue on the `PyIRoGlass GitHub repository <https://github.com/sarahshi/PyIRoGlass>`_, so future users can see an approach or resolution to the same problem. Select 'new issue' and make sure you provide information to trobuleshoot the problem, either by providing your Python notebook or screenshots of the entire error message. 
+``PyIRoGlass`` has been tested by several users, but it is still very possible that there are errors. Please alert `Sarah Shi <mailto:sarah.shi@columbia.edu>`_ to any errors or bugs within the code and/or raise an issue on the `PyIRoGlass GitHub repository <https://github.com/sarahshi/PyIRoGlass>`_, so future users can see an approach or resolution to the same problem. Select 'new issue' and make sure you provide information to trobuleshoot the problem, either by providing your Python notebook or screenshots of the entire error message. 

docs/introduction.rst

@@ -6,7 +6,7 @@ Welcome to ``PyIRoGlass``: An Open-Source, Bayesian MCMC Algorithm for Fitting B
 
 This tool is currently in progress, with submission to Volcanica in the near future. Please make sure you cite this tool if you use it. Software development takes time and and academia does not always recognize the effort taken, but it does recognize citations. 
 
-The open-source nature of the tool allows for continuous development. We welcome the submission of devolatilized FTIR spectra that can continue to shape the form of the baseline, and molar absorptivities. You can email `Sarah Shi <sarah.shi@columbia.edu>`_ or post an enhancement request or report of a bug on the issue page of the `PyIRoGlass GitHub repository <https://github.com/SarahShi/PyIRoGlass>`_. 
+The open-source nature of the tool allows for continuous development. We welcome the submission of devolatilized FTIR spectra that can continue to shape the form of the baseline, and molar absorptivities. You can email `Sarah Shi <mailto:sarah.shi@columbia.edu>`_ or post an enhancement request or report of a bug on the issue page of the `PyIRoGlass GitHub repository <https://github.com/SarahShi/PyIRoGlass>`_. 
 
 
 =============
@@ -15,7 +15,7 @@ Collaborators
 
 These folks have been fundamental to the development of ``PyIRoGlass``: 
 
-- `Sarah Shi <https://github.com/sarahshi>`_ (LDEO) `<sarah.shi@columbia.edu>`_
+- `Sarah Shi <https://github.com/sarahshi>`_ (LDEO) `sarah.shi@columbia.edu <mailto:sarah.shi@columbia.edu>`_
 - `Henry Towbin <https://github.com/whtowbin>`_ (LDEO)
 - `Terry Plank <https://github.com/terryplank>`_ (LDEO)
 - `Anna Barth <https://github.com/barthac>`_ (LDEO, Berkeley)

docs/submitting_data.rst

@@ -2,4 +2,4 @@
 Submitting data
 ===============
 
-We welcome the submission of devolatilized FTIR spectra that can continue to shape the form of the baseline, and molar absorptivities. You can email `Sarah Shi <sarah.shi@columbia.edu>`_, or post an enhancement request or report of a bug on the issue page of the `PyIRoGlass GitHub repository <https://github.com/SarahShi/PyIRoGlass>`_.
+We welcome the submission of devolatilized FTIR spectra that can continue to shape the form of the baseline, and molar absorptivities. You can email `Sarah Shi <mailto:sarah.shi@columbia.edu>`_, or post an enhancement request or report of a bug on the issue page of the `PyIRoGlass GitHub repository <https://github.com/SarahShi/PyIRoGlass>`_.

src/PyIRoGlass/__init__.py

@@ -548,45 +548,6 @@ def modelfit(data, uncert, indparams, model, title, nbins=75,
         plt.savefig(savefile)
     return ax, rax
 
-def subplotter(rect, margin, ipan, nx, ny=None, ymargin=None):
-
-    """
-    Create an axis instance for one panel (with index ipan) of a grid
-    of npanels, where the grid located inside rect (xleft, ybottom,
-    xright, ytop).
-    
-    Parameters: 
-        rect (1D np.ndarray): Rectangle with xlo, ylo, xhi, yhi positions of the grid boundaries.
-        margin (float): Width of margin between panels.
-        ipan (int): Index of panel to create (as in plt.subplots).
-        nx (int): Number of panels along the x axis.
-        ny (int): Number of panels along the y axis. If None, assume ny=nx.
-        ymargin (float): Width of margin between panels along y axes (if None, adopt margin).
-
-    Returns: 
-        ax (matplotlib.axes.Axes): Axes instance at the specified position.
-    """
-    if ny is None:
-        ny = nx
-    if ymargin is None:
-        ymargin = margin
-
-    # Size of a panel:
-    Dx = rect[2] - rect[0]
-    Dy = rect[3] - rect[1]
-    dx = Dx/nx - (nx-1.0)* margin/nx
-    dy = Dy/ny - (ny-1.0)*ymargin/ny
-    # Position of panel ipan:
-    # Follow plt's scheme, where panel 1 is at the top left panel,
-    # panel 2 is to the right of panel 1, and so on:
-    xloc = (ipan-1) % nx
-    yloc = (ny-1) - ((ipan-1) // nx)
-    # Bottom-left corner of panel:
-    xpanel = rect[0] + xloc*(dx+ margin)
-    ypanel = rect[1] + yloc*(dy+ymargin)
-
-    return plt.axes([xpanel, ypanel, dx, dy])
-
 
 # %%